| --- |
| library_name: transformers |
| language: |
| - jav |
| license: apache-2.0 |
| base_model: openai/whisper-small |
| tags: |
| - generated_from_trainer |
| datasets: |
| - SLR35 |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small Java |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: SLR Javanenese |
| type: SLR35 |
| args: 'config: java, split: train, test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 38.373095717160105 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # Whisper Small Java |
|
|
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SLR Javanenese dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9356 |
| - Wer: 38.3731 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.8832 | 0.1 | 100 | 0.9373 | 51.7965 | |
| | 0.3579 | 1.075 | 200 | 0.9986 | 51.4516 | |
| | 0.2348 | 2.05 | 300 | 0.9892 | 46.0765 | |
| | 0.1397 | 3.025 | 400 | 1.0404 | 47.0250 | |
| | 0.0836 | 3.125 | 500 | 0.9862 | 46.9531 | |
| | 0.0515 | 4.1 | 600 | 1.0148 | 42.2248 | |
| | 0.0222 | 5.075 | 700 | 0.9917 | 40.2846 | |
| | 0.0191 | 6.05 | 800 | 0.9665 | 39.3360 | |
| | 0.0078 | 7.025 | 900 | 0.9541 | 39.0486 | |
| | 0.0009 | 7.125 | 1000 | 0.9356 | 38.3731 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.51.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
|
|
